Enterprise environments typically generate log files to record a variety of activities. Sifting through the log file data sources to find errors and anomalies can be a daunting task, for example, due to the extensive volume of such log files. Analytics and semantic technologies may be applied to consume and analyze heterogeneous computer-generated log files to discover and extract relevant insights in a rationalized and structured form.